Data Engineer

SemiAnalysis; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

SemiAnalysis is seeking a clever and motivated Data Engineer to join our Singapore team. You’ll architect and maintain data models powering our industry models, research, and consulting work.

This role requires autonomy to work across our distributed team, ensuring data accuracy and robust, modular data systems for analytics and client delivery. Growth areas include data modeling and AI infrastructure exposure.

Qualifications

• 3+ years of experience in a Data Engineering, Data Science or reasonably equivalent role.
• Capable in Python, SQL, and Excel.
• Hands-on experience with at least one cloud platform (GCP, AWS, or Azure).
• Highly autonomous—able to take a problem from definition to deployment with minimal oversight.

Responsibilities

• Work with lead analysts to ensure data accuracy, completeness, and utility value across multiple sources and formats.
• Maintain and extend dashboards and APIs that deliver data to both internal analysts and external clients.
• Support the integration of new datasets, tools, and infrastructure components to enhance our analytics capabilities.
• Open-minded and resourceful with technical solutions and functionality of platforms.
• Maintain strong relationships with lead analysts and stakeholders to build solutions of the right fit.

Skills

Python

SQL

Excel

Tools

GCP

AWS

Azure

Job description

Find out more here: https://semianalysis.com

About SemiAnalysis

SemiAnalysis is an independent research and analysis firm specializing in the Semiconductor and AI industries. Our in-depth coverage spans the entire supply chain, from semiconductor fabrication processes to cutting-edge AI models, software, and infrastructure. We are recognized as the leading authority on the semiconductor supply chain, with the highest concentration of industry experts within one team, and a deep-rooted passion for delving into the intricacies.

We’re a global team of over 50 analysts, each with extensive networks across the semiconductor supply chain and AI ecosystem, publishing industry-shaping articles while participating in 40+ conferences annually.

Our newsletter reaches more than 200,000 subscribers worldwide, including senior management and C-suite leaders at the leading semiconductor and AI companies.

We also offer three core products:

• Industry Models – We develop and publish models on accelerator shipments, datacenter demand and supply, GPU total cost of ownership, and more.
• Core Research – We distill deep technical research into key insights on technology and product trends.
• Consulting and Technical Due Diligence – We conduct custom research and project work for the largest funds, leading venture-capital firms, companies across the AI ecosystem, and government agencies.

Position Overview

• We are seeking a clever and motivated Data Engineer to join our team in Singapore. You’ll be the architect and maintainer of the data models that power our industry models, research, and consulting work.
• This role requires a mix of technical expertise, autonomy, and pragmatism—you’ll need to work independently, collaborate across our globally distributed team, and build systems that are both accurate, robust, observable, and modular.
• If you have a favorite SCD type (mine’s Type 2), we should probably talk.

Responsibilities

• Work with lead analysts to ensure data accuracy, completeness, and utility value across multiple sources and formats.
• Maintain and extend dashboards and APIs that deliver data to both internal analysts and external clients.
• Support the integration of new datasets, tools, and infrastructure components to enhance our analytics capabilities.
• Open-minded and resourceful with technical solutions and functionality of platforms.
• Maintain strong relationships with lead analysts and stakeholders to build solutions of the right fit.

Requirements

• At least 3 years of experience in a Data Engineering, Data Science or reasonably equivalent role.
• Capable in Python, SQL, and Excel.
• Hands-on experience with at least one cloud platform (GCP, AWS, or Azure).
• Highly autonomous—able to take a problem from definition to deployment with minimal oversight.

Growth Areas

• Develop a deep understanding of data modelling in real-world industry contexts, not just pipelines, but how data drives decision-making and research narratives
• Gain exposure to cutting-edge domains including AI infrastructure, semiconductors, and datacenters
• Work closely with experienced analysts to bridge the gap between raw data and high-impact insights
• Take ownership of systems end-to-end, growing into someone who can design, scale, and maintain production-grade data architecture
• Build strong judgment on trade-offs between speed, accuracy, and scalability in a fast-moving research environment